Page 31 - Banking Finance November 2019

ARTICLE

experience to inform future decisions. Some of the Vision: It can be said as a field which enables the machines
decision-making functions in self-driving cars have been to see. Machine vision captures and analyses visual
designed in this way. Observations used to inform information using a camera, analog-to-digital conversion,
actions happening in the not so distant future, such a and digital signal processing. It can be compared to human
car that has changed lines. These observations are not eyesight but it is not bound by the human limitation which
stored permanently. can enable it to see through walls (now that would be
interesting if we can have implants that can make us see
3. Theory of Mind: This type of AI should be able to
understand people's emotions, belief, thoughts, through the wall). It is usually achieved through machine
expectations, and be able to interact socially. Even learning to get the best possible results so we could say that
though a lot of improvements are there in this field this these two fields are interlinked.
kind of AI is not yet implemented.
Robotics: It is a field of engineering focused on the design
4. Self-Awareness: An AI that has its own conscious, super and manufacturing of robots. Robots are often used to
intelligent, self-awareness and sentient (In simple words perform tasks that are difficult for humans to perform or
a complete human being). Ofcourse, this kind of bot also perform consistently. Examples include car assembly lines,
does not exist and if achieved it will be one of the in hospitals, office cleaner, serving foods, and preparing foods
milestones in the field of AI in hotels, patrolling farm areas and even as police officers.
Recently machine learning has been used to achieve certain
Key Components of Artificial Intelligence good results in building robots that interact socially.
Machine Learning (ML): It is a method where the target
(goal) is defined and the steps to reach that target is learned Autonomous Vehicles: This area of AI has gathered a lot
by the machine itself by training (gaining experience). For of attention. The list of vehicles includes cars, buses, trucks,
example to identify a simple object such as an apple or trains, ships, submarines, and autopilot flying drones etc.
orange. The target is achieved not by explicitly specifying
the details about it and coding it but it is just as we teach a Artificial Intelligence in Banking
child by showing multiple different pictures of it and Artificial Intelligence in banking is more than about chat
therefore allowing the machine to define the steps to bots. Here's why banks, especially in India, should consider
identify it like an apple or an orange. using the technology.

Natural Language Processing (NLP): Natural Language Banking business and technology leaders agree that Artificial
Processing is broadly defined as the automatic manipulation Intelligence (AI) is among the key trends that will reshape
of natural language, like speech and text, by software. One the banking industry.
of the well-known examples of this is email spam detection
as we can see how it has improved in our mail system. AI technologies such as machine learning, deep learning,
predictive/prescriptive analytics, virtual agents and natural
language understanding technologies (e.g. Sir, Alexa, Google
home) which were discussed above are gaining popularity
among progressive banks. Financial Services is data intensive
and therefore a great candidate for AI automation. AI
technologies offers banks an opportunity to reinvent banking
processes and gain unprecedented advantages.

Artificial Intelligence in Indian banking:
Challenges and opportunities
Artificial Intelligence (AI) is fast evolving as the go-to
technology for companies across the world to personalize
experience for individuals. The technology itself is getting
better and smarter day by day, allowing more and newer

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